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Service Quality in Electricity Distribution in Brazil: A Malmquist Approach

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  • Alexandre Marinho
  • Marcelo Resende

Abstract

The paper undertakes a dynamic analysis for service quality in the electricity distribution in Brazil between 2010 and 2014 based on Malmquist indexes constructed upon Data Envelopment Analysis (DEA) distance functions. The motivation for the less usual consideration of efficiency frontiers for service-quality builds on previous static applications in the context of telecommunications as given by Façanha and Resende (2004), Resende and Façanha (2005) and Resende and Tupper (2009). The analysis treats undesirable technical indicators as inputs and desirable consumer satisfaction indicators as outputs. The bootstrap- corrected Malmquist indexes indicated that service quality is an important concern as the evidence respectively indicates quality deterioration in 38.1 %, quality stagnation in 40.5 % and quality improvement only in 21.4 % of the cases. When one decomposes the Malmquist index, the evidence does not suggest relevant frontier shifts and indicates a dominant role for the catch-up effect.

Suggested Citation

  • Alexandre Marinho & Marcelo Resende, 2016. "Service Quality in Electricity Distribution in Brazil: A Malmquist Approach," CESifo Working Paper Series 6276, CESifo.
    • Handle: RePEc:ces:ceswps:_6276
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    References listed on IDEAS

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    1. de Souza, Fabio Cavaliere & Legey, Luiz Fernando Loureiro, 2010. "Dynamics of risk management tools and auctions in the second phase of the Brazilian Electricity Market reform," Energy Policy, Elsevier, vol. 38(4), pages 1715-1733, April.
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    3. Gianni De Fraja & Alberto Iozzi, 2008. "The Quest for Quality: A Quality Adjusted Dynamic Regulatory Mechanism," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 17(4), pages 1011-1040, December.
    4. Facanha, Luis Otavio & Resende, Marcelo, 2004. "Price cap regulation, incentives and quality:: The case of Brazilian telecommunications," International Journal of Production Economics, Elsevier, vol. 92(2), pages 133-144, November.
    5. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 2008. "The Measurement of Productive Efficiency and Productivity Growth," OUP Catalogue, Oxford University Press, number 9780195183528.
    6. Currier, Kevin M., 0. "A practical approach to quality-adjusted price cap regulation," Telecommunications Policy, Elsevier, vol. 31(8-9), pages 493-501, September.
    7. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    8. Peter Bogetoft & Lars Otto, 2011. "Benchmarking with DEA, SFA, and R," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7961-2, April.
    9. Wilson, Paul W., 2008. "FEAR: A software package for frontier efficiency analysis with R," Socio-Economic Planning Sciences, Elsevier, vol. 42(4), pages 247-254, December.
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    Cited by:

    1. Ryota Nakatani, 2023. "Productivity drivers of infrastructure companies: Network industries utilizing economies of scale in the digital era," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 94(4), pages 1273-1298, December.
    2. Yuan, Peng & Pu, Yuran & Liu, Chang, 2021. "Improving electricity supply reliability in China: Cost and incentive regulation," Energy, Elsevier, vol. 237(C).
    3. Resende, Marcelo & Cardoso, Vicente, 2019. "Mapping service quality in electricity distribution: An exploratory study of Brazil," Utilities Policy, Elsevier, vol. 56(C), pages 41-52.
    4. Nakatani, Ryota, 2022. "Productivity drivers of infrastructure companies: network industries to maximize economies of scale in the digital era," MPRA Paper 115531, University Library of Munich, Germany.
    5. Han, Yongming & Lou, Xiaoyi & Feng, Mingfei & Geng, Zhiqiang & Chen, Liangchao & Ping, Weiying & Lu, Gang, 2022. "Energy consumption analysis and saving of buildings based on static and dynamic input-output models," Energy, Elsevier, vol. 239(PC).

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    Keywords

    service quality; consumer satisfaction; electricity distribution; Brazil;
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